Abstract 2200: Transcriptomic profiling identifies an amino acid metabolism-related prognostic gene signature in lung adenocarcinoma patients
Authors: Huihui Xiang, Rika Kasajima, Hiroyuki Ito, Tomoyuki Yokose, Takashi Oshima, Tetsuro Sasada, Yohei Miyagi
Journal: Cancer Research (2023)

Abstract Lung cancer is by far the most common cancer-related fatality. In addition to the existing standard treatment methods, it is urgent to develop new therapy methods to improve the survival rate of patients. Amino acid metabolism plays a crucial role in tumor development. Cancer cells rely on amino acids for replication, energy source, redox homeostasis, and release metabolites that recruit and stimulate immunosuppressive cells. This study constructed a novel prognostic signature model of lung adenocarcinoma (LUAD) composed of amino acid metabolism-related genes and assessed immune cell infiltration characteristics and predictive value for patient therapy. We screened differentially expressed genes involved in amino acid metabolic pathways in LUAD tumor tissues versus normal tissues from RNA-seq data of The Cancer Genome Atlas. Then we performed a multivariate cox analysis of 9 genes significantly associated with patients’ overall survival, which established a new prognostic signature. Dividing the patients into high- and low-risk groups using a cutoff value of -0.36, the outcome showed that the risk score of this model could predict survival of LUAD patients with relatively high accuracy (ROC-AUC (max)=0.73). Subsequently, we utilized the ssGSEA method to quantify the infiltration of immune cells. We found that several immune cell subpopulations were significantly altered abundance between the high- and low-risk patients. Immune cell subpopulations, such as mast cell, plasmacytoid dendritic cell, and central memory CD4 T cell, were significantly abundant in the low-risk patients. After ESTIMATE algorithm evaluation, a method for estimating the proportion of stromal and immune cells in tumor tissues based on gene expression profiles, we observed that immune and stroma scores were markedly upregulated in low-risk patients, suggesting that the immune and stromal activity were increased. The key molecules of this signature exhibited a significant correlation with the expression of immune checkpoint molecules. Moreover, multivariate cox regression model analysis was performed with patients’ age, gender, clinical stage, T stage, M stage, N stage and risk score. The results indicated that the risk score signature was a significant and independent prognostic biomarker for the prognostic prevision of LUAD patients.Finally, the risk score based on the amino acid metabolism-related signature was successfully validated by the data of LUAD patients in the GEO dataset GES30219.These findings suggest that the prognostic signature based on the expression of genes involved in amino acid metabolism may be useful and effective. We further characterized one of the 9 genes involved in tryptophan metabolism for its biological implications in tumor progression and construction of immuno-suppressive tumor microenvironment by experimental procedures with human LUAD cell lines. Citation Format: Huihui Xiang, Rika Kasajima, Hiroyuki Ito, Tomoyuki Yokose, Takashi Oshima, Tetsuro Sasada, Yohei Miyagi. Transcriptomic profiling identifies an amino acid metabolism-related prognostic gene signature in lung adenocarcinoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2200.